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Synthetic data framework to estimate the minimum detectable concentration of contrast agents for multispectral optoacoustic imaging of small animals
Author(s) -
Yang Hong,
Olefir Ivan,
Tzoumas Stratis,
Ntziachristos Vasilis
Publication year - 2019
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201900021
Subject(s) - multispectral image , contrast (vision) , in vivo , experimental data , biomedical engineering , synthetic data , biological system , computer science , materials science , artificial intelligence , medicine , mathematics , biology , statistics , microbiology and biotechnology
The concentrations of contrast agents for optoacoustic imaging of small animals must usually be optimized through extensive pilot experiments on a case‐by‐case basis. The present work describes a streamlined approach for determining the minimum detectable concentration (MDC) of a contrast agent given experimental conditions and imaging system parameters. The developed Synthetic Data Framework (SDF) allows estimation of MDCs of various contrast agents under different tissue conditions without extensive animal experiments. The SDF combines simulated optoacoustic signals from exogenously administered contrast agents with in vivo experimental signals from background tissue to generate realistic synthetic multispectral optoacoustic images. In this paper, the SDF is validated with in vivo measurements and demonstrates close agreement between SDF synthetic data and experimental data in terms of both image intensity and MDCs. Use of the SDF to estimate MDCs for fluorescent dyes and nanoparticles at different tissue depths and for imaging lesions of different sizes is illustrated.